Process variable

About: Process variable is a research topic. Over the lifetime, 3983 publications have been published within this topic receiving 43130 citations. The topic is also known as: process parameter.

Morphological studies of blends containing liquid crystalline polymers with poly(ethylene terephthalate)

Abstract: The investigation involved the structure–property behavior of extruded cast films prepared from blends of thermotropic liquid crystalline copolyesters with poly(ethylene terephthalate) (PET). Data were obtained which showed not only the temperature dependence of the moduli and stress–strain behavior but also the orientation effects that must be prevalent in order to explain the differences between the moduli measured parallel and perpendicular to the extrusion direction. Only at high liquid crystal polymer (LCP) composition is the modulus particularly increased. The modulus enhancement with lower LCP content and utilization of process variables are discussed with respect to the induced morphological textures and nature of the process equipment. Specifically, the process variable extruder gear pump speed did not enhance Young's modulus at the same LCP content as extensively as did the process variable of extruder screw speed.

Comparative Study of the Sensitivity of PLA, ABS, PEEK, and PETG’s Mechanical Properties to FDM Printing Process Parameters

Abstract: Significant advances in fused deposition modeling (FDM), as well as its myriad applications, have led to its growing prominence among additive manufacturing (AM) technologies. When the technology was first developed, it was used for rapid prototyping to examine and analyze a product in the design stage. FDM facilitates rapid production, requires inexpensive tools, and can fabricate complex-shaped parts; it, therefore, became popular and its use widespread. However, various FDM processing parameters have proven to affect the printed part’s mechanical properties to different extents. The values for the printing process parameters are carefully selected based on the part’s application. This study investigates the effects of four process parameters (raster angle, layer thickness, infill percentage, and printing speed) on the mechanical behavior of printed parts that are based on available literature data. These process parameter’s influence on part’s mechanical properties varies depending on the FDM material. The study focuses on four FDM materials: polylactic acid (PLA), acrylonitrile butadiene styrene (ABS), polyether ether ketone (PEEK), and polyethylene terephthalate glycol (PETG). This paper summarizes the state-of-the-art literature to show how sensitive the material’s mechanical properties are to each process parameter. The effect of each parameter on each material was quantified and ranked using analysis of variance (ANOVA). The results show that infill percentage then layer thickness are the most influential process parameter on most of the material’s mechanical properties. In addition, this work identifies gaps in existing studies and highlights opportunities for future research.

Prediction and optimization of process parameter of friction stir welded AA5083-H111 aluminum alloy using response surface methodology

Abstract: A systematic approach was presented to develop the empirical model for predicting the ultimate tensile strength of AA5083-H111 aluminum alloy which is widely used in ship building industry by incorporating friction stir welding (FSW) process parameters such as tool rotational speed, welding speed, and axial force. FSW was carried out considering three-factor five-level central composite rotatable design with full replications technique. Response surface methodology (RSM) was applied to developing linear regression model for establishing the relationship between the FSW process parameters and ultimate tensile strength. Analysis of variance (ANOVA) technique was used to check the adequacy of the developed model. The FSW process parameters were also optimized using response surface methodology (RSM) to maximize the ultimate tensile strength. The joint welded at a tool rotational speed of 1 000 r/min, a welding speed of 69 mm/min and an axial force of 1.33 t exhibits higher tensile strength compared with other joints.

Endpoint detection in substrate fabrication processes

Abstract: In an endpoint detection method for a process performed in a substrate processing chamber with an energized gas, a process variable of the process is detected. The process variable comprising at least one of (i) a radiation emitted by the energized gas, (ii) a radiation reflected from a substrate in the chamber, (iii) a reflected power level of the energized gas, and (iv) a temperature in the chamber. An endpoint signal is issued when the process variable is indicative of an endpoint of the process. A process parameter of the process is also detected, the process parameter comprising at least one of (i) a source power, (ii) an RF forward power, reflected power, or match components, (iii) an RF peak-to-peak voltage, current or phase, (iv) a DC bias level, (v) a chamber pressure or throttle valve position, (vi) a gas composition or flow rate, (vii) a substrate temperature or composition, (viii) a temperature of a chamber component or wall, and (ix) a magnetic confinement level or magnet position. The endpoint signal is determined to be true or false by evaluating the process parameter.

Multiresponse optimization based on statistical response surface methodology and desirability function for the production of particleboard

Abstract: It is very difficult to determine the actual level of process parameters responsible for the quality production of particleboard due to the high degree of process variable interactions and lack of robust methodology for optimization. In this study, an attempt was made to optimize the process parameters of particleboard production by using multi-response optimization process. Plackett–Burman factorial design was first employed to eliminate some factors from selected seven important parameters: flake thickness, flake length, dried chips moisture content (MC%), amount of adhesive, pressing time, pressure, and press temperature. By using this screening procedure, three important factors: flake thickness, dried chips moisture content and press temperature were found to have significant effect on particleboard properties. Afterwards, Box–Behnken design was performed as response surface methodology (RSM) with desirability functions to attain the optimal flake thickness, MC% and press temperature that affect modulus of rapture (MOR) and modulus of elasticity (MOE) of particleboard production. The optimized parameters for maximum MOR and MOE determined were found to be: flake thickness, 0.15 mm; press temperature, 182 °C; and dried chip MC% 3.5. Finally, a confirmation study was executed by using optimized levels of parameters which showed well response to the predicted model.